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首页> 外文期刊>Intelligent Transportation Systems, IEEE Transactions on >Nonlinear Coordinated Steering and Braking Control of Vision-Based Autonomous Vehicles in Emergency Obstacle Avoidance
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Nonlinear Coordinated Steering and Braking Control of Vision-Based Autonomous Vehicles in Emergency Obstacle Avoidance

机译：紧急避障中基于视觉的自动驾驶车辆的非线性协调转向和制动控制

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摘要

This paper discusses dynamic control design for automated driving of vision-based autonomous vehicles, with a special focus on the coordinated steering and braking control in emergency obstacle avoidance. An autonomous vehicle is a complex multi-input and multi-output (MIMO) system, which possesses the features of parameter uncertainties and strong nonlinearities, and the coupled phenomena of longitudinal and lateral dynamics are evident in a combined cornering and braking maneuver. In this work, an effective coordinated control system for automated driving is proposed to deal with these coupled and nonlinear features and reject the disturbances. First, a vision algorithm is constructed to detect the reference path and provide the local location information between vehicles and reference path in real time. Then, a novel coordinated steering and braking control strategy is proposed based on the nonlinear backstepping control theory and the adaptive fuzzy sliding-mode control technique, and the asymptotic convergence of the proposed coordinated control system is proven by the Lyapunov theory. Finally, experimental tests manifest that the proposed control strategy possesses favorable tracking performance and enhances the riding comfort and stability of autonomous vehicles.
机译：本文讨论了基于视觉的自动驾驶汽车自动驾驶的动态控制设计，特别着重于紧急避障中的协调转向和制动控制。自动驾驶汽车是一种复杂的多输入多输出（MIMO）系统，具有参数不确定性和强烈的非线性特性，在转弯和制动动作组合中，纵向和横向动力学的耦合现象显而易见。在这项工作中，提出了一种有效的自动驾驶协调控制系统，以处理这些耦合和非线性特征并消除干扰。首先，构造视觉算法以检测参考路径并实时提供车辆和参考路径之间的局部位置信息。然后，基于非线性反步控制理论和自适应模糊滑模控制技术，提出了一种新颖的协调转向和制动控制策略，并利用李雅普诺夫理论证明了该协调控制系统的渐近收敛性。最后，实验测试表明，提出的控制策略具有良好的跟踪性能，提高了自动驾驶汽车的乘坐舒适性和稳定性。

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